5 citations · 30 across the 19 of their papers we have counts for
19 papers
Exploring Reasoning Biases in Large Language Models Through Syllogism: Insights from the NeuBAROCO Dataset
Kentaro Ozeki, Risako Ando, Takanobu Morishita +3
This paper explores the question of how accurately current large language models can perform logical reasoning in natural language, with an emphasis on whether these models exhibit…
Evaluating Large Language Models with NeuBAROCO: Syllogistic Reasoning Ability and Human-like Biases
Risako Ando, Takanobu Morishita, Hirohiko Abe +2
This paper investigates whether current large language models exhibit biases in logical reasoning, similar to humans. Specifically, we focus on syllogistic reasoning, a well-studie…
Compositional Evaluation on Japanese Textual Entailment and Similarity
Hitomi Yanaka, Koji Mineshima
Natural Language Inference (NLI) and Semantic Textual Similarity (STS) are widely used benchmark tasks for compositional evaluation of pre-trained language models. Despite growing…
Building a Video-and-Language Dataset with Human Actions for Multimodal Logical Inference
Riko Suzuki, Hitomi Yanaka, Koji Mineshima +1
This paper introduces a new video-and-language dataset with human actions for multimodal logical inference, which focuses on intentional and aspectual expressions that describe dyn…
SyGNS: A Systematic Generalization Testbed Based on Natural Language Semantics
Hitomi Yanaka, Koji Mineshima, Kentaro Inui
Recently, deep neural networks (DNNs) have achieved great success in semantically challenging NLP tasks, yet it remains unclear whether DNN models can capture compositional meaning…
Visual representation of negation: Real world data analysis on comic image design
Yuri Sato, Koji Mineshima, Kazuhiro Ueda
There has been a widely held view that visual representations (e.g., photographs and illustrations) do not depict negation, for example, one that can be expressed by a sentence "th…